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DNA's Trap for Investors: A Race to the Bottom

By Adam J. Crawford, Junior Analyst

DNA sequencing is generating a lot of excitement these days. It's easy to understand why, given the glowing growth forecasts that have hit the news. A recent BCC Research Study projects that the sequencing market will reach $6.6 billion by 2016; that is more than double its current value of roughly $3 billion and represents a CAGR of 17.5%. Out front will be the services market, which is expected to expand by 29%, jumping from about $987 million to $3.5 billion by 2016. The instruments and consumables market, along with workflow products, are expected to expand as well, although at a slower rate. Some have even gone as far as to say that DNA sequencing could eventually evolve into a $100 billion market.

But before diving headlong into investment opportunities in the DNA space, chasing that elusive birdie, there is one big trap that investors need to be aware of.

Sequencing Simplified

First, for the uninitiated, we must understand what's behind all the enthusiasm for this groundbreaking technology.

DNA sequencing aims to read a piece of DNA like a book - to determine the order of the bases in a strand of DNA, which is composed of an amazingly simple string of chemicals, each of which is typically represented by one of four letters. A sample DNA sequence might look something like this:

The next step involves interpreting these results. For example, a scientist might study the sequence and attempt to identify various patterns that exist. Doing so could provide solutions to a whole host of problems. (Biology buffs or anyone who's a glutton for punishment may wish to learn more about how to sequence DNA.)

Potential and Current Uses

DNA sequencing has a host of uses, most rooted in medicine, though with quite a few outside of the field as well, in everything from anthropology to criminology. Despite that range, it is still an early-stage science. Today, scientists spend the majority of their time searching for what exactly the 23 chromosomes (ranging in size from 50 million to 250 million bases each) and the 23,000 or so genes those chromosomes contain actually do. They are looking for the genes responsible for horrible diseases, from cancer to Huntington's disease. Once such a gene is found, they test potential genetic-level cures against those genes. It's a very much a trial-and-error process that involves taking hundreds, thousands, or even millions of samples for testing and analysis.

But as our understanding of the biology of DNA improves over time, the possibilities for using that knowledge are virtually endless. Futurists and experts in the field have postulated all kinds of fascinating scenarios.

Sequencing of full genomes could potentially be used in the field of criminology. For instance, it may soon be possible to sequence the DNA evidence obtained at a crime scene and use the information to construct a life-size replica of the perpetrator of a crime. The same applies to the victim of a crime (in cases where the identity is unknown).
This technology could possibly be used to map out "brain" DNA sequences of two people, compare them, and determine what makes one person smarter than  the other. In doing so, scientists could potentially alter the "brain" DNA sequence of the intellectually challenged to more closely resemble that of an individual with superior intellect. I suppose the opposite effect could also be achieved, if one so desires. A similar altering technique could potentially be used to "improve" one's genetic composition in several different ways (shorter to taller, weaker to stronger, etc.).
Of course, sequencing technology has a ways to go before it reaches this point. And even if it does, the ability to alter an individual's genetic composition will likely face intense public scrutiny, thus reducing the odds it will occur. But the potential remains intriguing.

Perhaps the most immediate and meaningful societal impact DNA sequencing will have is in its ability to provide a personalized healthcare experience.

For example, once a DNA sample is submitted and sequenced, it can then be analyzed to determine one's predisposition for a specific disease or group of diseases. This information can also be used to identify potentially problematic genes that could be inherited by one's offspring. This is important because, once identified, the disease may be treated before it progresses to a critical state. It may even be possible to prevent the disease altogether (one company in our "curing cancer" portfolio is creating drugs that instruct genetic "filters" to block disorders in people genetically predisposed to developing them).

DNA sequencing is also used to identify the best treatment for an individual when a health problem already exists. For example, sequencing results might reveal that the most effective breast cancer treatment for a specific patient is something other than a grueling, potentially dangerous, and often overprescribed chemotherapy regimen. Furthermore, sequencing has proven effective in identifying and treating existing conditions that were previously unidentifiable and therefore untreatable.

DNA sequencing can also take the guesswork out of prescribing certain drugs for an individual. In the future, sequencing could even lead to the development of new innovative drugs.

These are just a few examples of the current and potential applications of this technology. There are many more. This is cause for great excitement it in itself, but especially so when considering trends in costs and speed for both diagnosis and treatment of medical conditions.

Sequencing Costs and Speed

One might expect to pay a lofty price for access to this cutting-edge technology, but that is not the case. Sequencing a whole genome (a person's complete DNA blueprint) is a relative bargain considering the price to sequence a genome just a few short years ago. As shown below, the cost per genome is outpacing Moore's law, an indication that it is performing exceedingly well.

At the same time, sequencing speed is increasing at an impressive rate. Consider that the initial mapping of the human genome was begun by the Human Genome Project in 1990 and was not completed until 2003 (at a cost of about $3 billion). Today, machines with superfast, sequencing-specific chips are capable of basic decoding in a single day. And even that will be reduced to a matter of hours in the near future.

The practical value of the technology was demonstrated during the E. coli outbreak in Germany last year, when scientists sequenced the DNA of the outbreak-causing bacterium in just a couple of hours. Such quick responses to public-health crises can mean the difference between life and death.

Add blazing speed to the plummeting cost per genome, and it's pretty easy to predict a huge increase in demand. A New York Times article from November of 2011 stated, "There will probably be 30,000 human genomes sequenced by the end of this year, up from a handful a few years ago, according to the journal Nature. And that number will rise to millions [emphasis ours] in a few years."

Data Overload

One major problem going forward is handling and analyzing the substantial volume of sequencing data - not to mention doing so in a timely and cost-effective manner. David Haussler, director of the Center for Biomolecular Science and Engineering at the University of California, Santa Cruz, said in the Times article, "Data handling is now the bottleneck. It costs more to analyze a genome than to sequence a genome."

And it's not just the cost of analysis. There is also the logistical nightmare of moving mountains of data. As the Times noted:

"BGI, based in China, is the world's largest genomics research institute, with 167 DNA sequencers producing the equivalent of 2,000 human genomes a day. BGI churns out so much data that it often cannot transmit its results to clients or collaborators over the Internet or other communications lines because that would take weeks. Instead, it sends computer disks containing the data, via FedEx. 'It sounds like an analog solution in a digital age,' conceded Sifei He, the head of cloud computing for BGI ... But for now, he said, there is no better way."

These concerns are creating an atmosphere of uncertainty regarding the mass adoption of this innovative technology. However, many bioinformatics firms are working on ways to address the problem. Google is also joining the effort. We expect many more to follow.

This will create good investment opportunities. According to Isaac Ro, an analyst at Goldman Sachs, "We believe the field of bioinformatics for genetic analysis will be one of the biggest areas of disruptive innovation in life science tools over the next few years."

The Trap

Analysis may be a surefire growth industry, but what about the sequencing itself? Isn't that as good a place to invest, if not better?

Yes, there will be opportunities. But they're trickier in this part of the space. A lot of companies are jockeying for position. There are at least a half-dozen different technologies in play and numerous subsets of those. New approaches pop up seemingly every few months or so. This means that the competition is intense, and the winnowing process is going to be painful for many.

Take Illumina (ILMN), for instance. Right now, it is one of the biggest players, with its executives crowing that the company is "the Apple of the genomics business." Well, this comparison is accurate if they are referring to the fact that the company sells pricey equipment (which isn't even as impressive from a technological standpoint as the machines from PACB). But, unlike with Apple devotees - who will pay more for what they consider to be higher quality - in DNA sequencing cost is everything.

It's essentially a race to the bottom. Whoever provides machines that do the work cheaper will rule the roost... at least temporarily, until the next hot tech comes along. If you make better equipment but your costs are higher, you're apt to lag the market regardless of the relative precision of your machine.

In the future, if full genome sequencing falls to $50, as many are predicting - and as the data-handling problem is resolved - then the last company standing may be the one that provides the service, like Complete Genomics (GNOM). Everyone else will simply do the most cost-effective thing and outsource the job.

In sum, as this technology takes off, there will be winners and losers. The key to successful investing will be the ability to separate the former from the latter.

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